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According to Bloomberg, citing Smart Analytics Global data, the global shipment of humanoid robots in the first half of 2026 is approximately 19,100 units, a year-on-year increase of over 200% (compared to about 5,100 units in the same period last year), with Chinese manufacturers accounting for over 97%. The agency expects the total shipment for the year 2026 to reach about 60,000 units, and it is anticipated to grow to 500,000 units by 2030.The report points out that China has formed an early leading advantage over American competitors in the field of humanoid robots. Previously, Morgan Stanley raised its forecast for China's humanoid robot shipments in 2026 to 50,000 units, and IDC data also shows that the top five companies in global humanoid robot shipments in 2025 will all be Chinese firms, while American companies Figure AI and Tesla rank seventh and ninth, respectively.

According to the industry analysis platform Hello China Tech, as of June 2026, there are a total of 8 humanoid robot-related companies in China with valuations reaching or exceeding 20 billion yuan (approximately 2.9 billion USD), of which 5 companies have valuations primarily based on models rather than shipment volumes, with annual shipment volumes still maintaining at the hundreds level. In the second quarter, the financing amount in the humanoid robot field reached 6.95 billion USD, more than double that of the previous quarter.The report points out that the data collection costs vary significantly across different stages: the hourly wage for frontline operators is about 20 to 40 yuan, approximately 25 yuan when outsourced; the internal cost for companies involving robots is about 250 yuan; and the data price from government-supported training bases reaches 500 to 1000 yuan. However, the data produced through different collection methods (wearable devices and robot involvement) shows significant differences in quality and training effectiveness, with only about 50 hours of usable data from 100 hours of raw collection. The data measurement units used by different companies (hours, trajectories, skills, etc.) are incompatible, and there is a lack of independent auditing, leading to considerable uncertainty in valuation bases. It is believed that the industry urgently needs to establish a unified data asset measurement standard.

According to La Tribuna, the body of a Chinese man was found outside the Jade Park high-rise apartment in the Trinidad district of Asunción, Paraguay. Preliminary identification confirmed the identity as Harry Chun Tak Yeh, the founder and managing partner of Quantum Fintech Group. The police stated that he is suspected to have fallen from the 30th floor of the building, and his body was found completely naked and covered with a black plastic bag. Investigators found the apartment door on the 30th floor ajar, with the interior in disarray, and confirmed that he also owned another apartment on the 27th floor of the same building. Criminal technicians have collected evidence outside the building and from both apartments, and relevant physical evidence has been handed over to the prosecution. The prosecution is currently investigating multiple possibilities, including accident, suspected suicide, and homicide, while the judicial department will determine the specific cause of death and the circumstances through an autopsy.It is reported that Chinese-American cryptocurrency investor Harry Yeh entered the Bitcoin market in 2013 when the BTC trading price was $60. He launched his first fund with $250,000, and his investment network claims to manage over $2.4 billion in assets, closely linked with Fantom, Tomb Finance, Lif3, ZooCoin, L3 USD, and L3 Reserve.

According to information from the official Apple website, Apple Smart has supported collaboration with Alibaba's Qianwen model.According to the official introduction, after users enable the relevant features, Siri can use the Qianwen model to provide more in-depth answers, including analyzing photos and documents; the writing tool can also leverage Qianwen to generate text or image content based on user descriptions.

According to Bloomberg, informed sources revealed that the U.S. government department responsible for investigating violations of chip export controls is currently conducting a systematic review of how Chinese AI companies obtain advanced chips from Nvidia through legal means, focusing on their behavior of renting computing power in third countries. This move stems from recent technological breakthroughs achieved by Chinese AI companies, indicating that they still have the capability to acquire and use top-tier hardware despite U.S. export restrictions on chips to China. Analysts believe that this review may prompt the U.S. to further tighten regulatory rules on computing power leasing in third countries to close existing loopholes in the export control system.

According to The New York Times, Chinese AI models are rapidly gaining popularity in the African developer community due to their low cost, open-source customization, and better handling of local languages, while leading American models like OpenAI and Anthropic are primarily closed-source and paid. Ugandan developer Ernest Mwebaze chose Alibaba's model over Meta or Google products when building a multilingual AI system called Sunflower aimed at local languages, which is now widely used by local farmers to obtain weather and planting information.The report states that similar adoption trends are spreading in countries like Kenya, Nigeria, and Ghana, covering multiple fields such as law, education, and business services. Chinese open-source models (such as DeepSeek and Qianwen) allow for free download and modification, while leading American models are often closed-source and paid, creating significant cost and accessibility differences in middle- and low-income countries. Industry insiders point out that the rapid penetration of Chinese AI in Africa is bringing long-term competitive pressure to American AI giants.

According to Jinshi reports, Nvidia is urgently seeking AI base station suppliers in China to develop 6G AI-RAN base stations, which are responsible for both communication connections and AI computing. Nvidia hopes to enter the trial network in 2027 or 2028, and Shenzhen Jiaxian Communication is one of its partners. The two parties have been collaborating on the development of 6G AI-RAN base stations based on Nvidia's CUDA ecosystem for more than six months.

According to Counterpoint Research analysis, if the proposed import ban on Chinese optical modules by the Federal Communications Commission (FCC) in the United States is implemented, it will primarily impact American cloud providers rather than Chinese suppliers. InnoLight leads the global data center optical module revenue with approximately 27% market share, while Coherent ranks second with about 17%. Chinese manufacturers collectively account for about two-thirds of the global unit supply and approximately 60% of the optical communication module revenue.The analysis points out that Western suppliers like Coherent and Lumentum lack sufficient cleanroom capacity, automated packaging infrastructure, and yield scale in the short term, making it impossible to fill the capacity gap left by Chinese manufacturers within 12-24 months. This could lead to delays in AI cluster deployments by several quarters and increase material costs for cloud providers. At the same time, Chinese module manufacturers rely on high-end 800G/1.6T module revenue from North American hyperscale customers for over 90%, but have achieved partial capacity relocation by establishing factories in Thailand.Counterpoint emphasizes that the optical module supply chain is a highly interdependent system. Chinese manufacturers heavily procure DSP chips from Broadcom and Marvell, as well as lasers and optical chips from Lumentum, Coherent, and Mitsubishi Electric. A forced separation would disrupt the entire ecosystem.

According to Jinshi, the United States plans to ban the import of new data center equipment from China.The Chinese Embassy in the United States urges the U.S. to stop smearing Chinese companies and threatening sanctions.

According to Reuters, citing four informed sources, the Trump administration is drafting a ban on the import of new models of optical modules for data centers from China. The Federal Communications Commission (FCC) is formulating this measure to prohibit the import of new models of optical modules that can transmit data through fiber optic cables within data centers, with officials hoping to release and implement it within this year. The ban aims to prevent Chinese companies from stealing data, implanting malware, or disrupting services at U.S. data centers.The ban may primarily affect Inspur (leading with a 27% share of the global data center optical module market), which was listed in June of this year on the Pentagon's list of companies involved in military activities. U.S. cloud providers (such as AWS) may be forced to turn to alternative suppliers like Coherent and Lumentum, raising costs. The FCC has previously imposed similar restrictions on Chinese drones, routers, robots, and inverters. The Chinese embassy in the U.S. stated that "it will take all necessary measures to respond to any actions that harm China's interests." The draft may still be modified or shelved.

Researchers at the Chinese People's Public Security University have developed an AI framework capable of detecting illegal cryptocurrency transactions with an overall accuracy rate close to 90%. The study was published in the Chinese peer-reviewed journal "Journal of Intelligence," and the corresponding author, Dr. Sun Jingchao (specializing in criminal investigation and cybersecurity), noted that the research "provides an accurate, scalable, and interpretable solution for detecting illegal cryptocurrency transactions," and offers "an innovative technical path" for regulatory agencies to combat illegal cryptocurrency transactions and economic crimes.This AI framework utilizes memory modules and large language models, specifically targeting the anonymity and cross-border characteristics of cryptocurrencies to track illegal activities such as money laundering. The release of this research coincides with China's ongoing efforts to intensify the crackdown on financial crimes related to cryptocurrencies. In March of this year, the Supreme People's Procuratorate of China disclosed that by 2025, procuratorial authorities had prosecuted 3,259 individuals for money laundering crimes involving virtual currencies and underground banks.As the trading volume of cryptocurrencies rapidly increases, their anonymity and cross-border characteristics provide a channel for illegal fund flows. This police-developed AI detection tool marks a shift in regulatory technology from passive tracking to proactive intelligent identification.

Galaxy Research Research Director Alex Thorn stated that the attack targeting Coldcard wallet address generation is still ongoing. They are currently continuing to collect victim information and adding new victim addresses and attacker addresses to the investigation database.If users are still using affected Coldcard single-signature addresses, they should immediately migrate their funds. According to current investigation results, all single-signature Coldcard addresses generated after the firmware upgrade in March 2021 may ultimately be emptied by attackers; it is just a matter of time.According to Galaxy Research's analysis, the first three confirmed rounds of attacks exhibit highly programmatic characteristics, with similar attack transaction patterns. A large amount of stolen Bitcoin remains in the attackers' addresses and has not yet been transferred.At the same time, some new opportunistic attackers are emerging, transferring and laundering funds through methods such as stripping the funding chain, cross-chain services (like ThorChain), and overseas betting platforms.Additionally, Alex Thorn mentioned the limitations of AI tools in security investigations. Some large language models in the United States have restricted researchers' ability to track stolen funds, and the team has even had to turn to Chinese open-source AI models to assist in protecting user assets and conducting on-chain tracking.He finds this phenomenon "incredible" and plans to promote discussions on related issues at the government and industry levels. Alex Thorn concluded by stating that a large amount of stolen funds remains stagnant, and the team is continuously tracking relevant addresses, having shared information with relevant U.S. agencies and industry partners. He calls on the Bitcoin community to learn from this incident, strengthen self-custody security education, and raise awareness of wallet complexity.

According to the Financial Times, after three years of record low stagnation, Chinese venture capital firms are accelerating the fundraising of new funds, seeking to capitalize on investors' renewed interest in the Chinese technology sector.Data from Asante Capital shows that at least 60 new dollar funds are planning to raise a total of about $35 billion, of which about 40 are venture capital funds. HSG, IDG Capital, Matrix Partners China, and Ming Shi Capital are promoting new funds or preparing to start fundraising, while ZhenFund and Qiming Venture Partners have recently completed fundraising.The successful listings of technology companies such as Zhipu and MiniMax, as well as progress in projects like The Dark Side of the Moon, DeepSeek, and the robotics field, have prompted investors to refocus on Chinese technology. Some investors view allocating to Chinese AI as a way to hedge bets on the U.S. market, as Chinese companies are highly competitive on costs and offer lower-priced model services.However, market participants indicate that this does not mean Chinese venture capital has returned to a boom period, but rather that dollar fundraising has selectively restarted after three consecutive years of low levels.Preqin data shows that in 2022, a total of 1,105 China-related funds raised $150 billion, while in 2025, only 97 funds raised $13.6 billion.Currently, some large U.S. investors remain cautious due to restrictions on sensitive technology investments, while European and Middle Eastern funds show stronger interest. Investors are vying for more co-investment rights in the current "buyer’s market" and are demanding fund managers to invest more of their own capital. Meanwhile, a large amount of capital is competing for a limited number of high-confidence projects, particularly concentrated in the AI sector.

According to X user Rohan Paul, when the OpenAI model breached Hugging Face, Anthropic's Claude 5 refused to assist in the investigation, and Hugging Face ultimately turned to Nvidia's quantized version of GLM 5.2 for emergency response.The user commented that banning open-source models would weaken the defense's capabilities, and this incident confirms the practical value of open-source models in security response.

According to Jinshi reports, the Ministry of Commerce stated that the U.S. practice of including Chinese companies in the so-called Xinjiang-related entity list has no factual basis and is a typical act of economic coercion. The U.S. measures seriously harm the legitimate rights and interests of the relevant enterprises and undermine the stability of global industrial and supply chains.China urges the U.S. to immediately stop its attacks and smear campaigns against Xinjiang, cease manipulating the so-called "forced labor" issue, and will take necessary measures to firmly safeguard the legitimate rights and interests of Chinese enterprises.

Ronald Keung, the head of Asian Internet Research at Goldman Sachs, stated that as the global usage of Chinese AI models surges, developers may begin to charge commercial licensing fees to cloud platforms for hosting their open-weight models. Currently, most Chinese models are released under permissive licenses such as the MIT License, allowing any user to use, modify, and host them for free, including for commercial purposes.Keung pointed out that Chinese AI models like Kimi K3 from the Dark Side of the Moon and GLM-5.2 from Zhiyu AI have performance levels that are close to those of leading models in the United States. The adoption rate among small and medium-sized enterprises, both domestically and globally, is very fast, and even large enterprises are beginning to consider using Chinese models. Goldman Sachs believes that model developers can convert the growing use of open-source into actual revenue by requiring third-party service providers to purchase commercial licenses to run model inference on their own infrastructure.

According to the latest survey by TrendForce, in June, the top three MLCC suppliers in Japan and South Korea (Murata, Samsung Electro-Mechanics, Taiyo Yuden) achieved a monthly shipment volume that reached a nearly five-year high, with 140 billion, 98 billion, and 40 billion units respectively, and the growth momentum continued into July. AI applications are the main driving force, with CSP manufacturers maintaining strong procurement demand for self-developed ASIC platforms such as Google TPU and AWS Trainium, driving continuous growth in demand for high-capacity, low-voltage, small-sized MLCCs.At the same time, Japanese and South Korean suppliers are accelerating the shift of production capacity from consumer-grade X5R to high-end X6S/X7R specifications, resulting in a severe squeeze on the production capacity of mid-to-high capacity (1µF-22µF) consumer-grade MLCCs, with mainstream inventory days generally falling below 30 days. The overflow effect of production capacity has led channels, agents, and second- and third-tier customers to urgently pull goods, significantly increasing order visibility for Taiwanese and mainland suppliers, leading to rising prices, with agents raising prices by an average of 20-25%, and spot market prices have soared to 2-3 times the original price. TrendForce pointed out that the consumer-grade MLCC market currently shows a structural mismatch of "weak end demand, strong channel pricing."

A spokesperson for the Chinese Ministry of Commerce responded to the U.S. claim that it would investigate Chinese AI companies for "distilling" U.S. cutting-edge models and may impose sanctions, stating that this move lacks factual and legal basis and is a typical act of artificial intelligence hegemony.China pointed out that some of its model capabilities are already at the leading level, and nearly 200 U.S. startups urged the government not to cut off access to Chinese open-source models. China urged the U.S. to stop the smear campaign and threats of sanctions; otherwise, it will take all necessary measures to safeguard its own rights and interests.

According to Reuters, citing informed sources, due to the surge in demand for AI data centers leading to a tight supply of server CPUs, Intel and AMD are negotiating long-term procurement commitments with Chinese server customers. Agreements typically lock in a year's supply, with some discussions extending to two years or longer. Driven by the construction of AI computing power, CPU demand has expanded from AI accelerators to mainstream processors, with some server CPU products in the Chinese market experiencing a cumulative price increase of over 40% this year, with month-on-month increases exceeding 10% at times.Intel CEO Lip-Bu Tan stated in April that Xeon server CPU demand "continues to exceed supply," and the company has signed multiple long-term contracts in the first quarter, including a multi-year agreement with Google. AMD has raised its forecast for the server CPU market to exceed $120 billion by 2030. The report notes that China, as one of the largest server markets in the world, is intensifying competition for Intel and AMD processors due to the rapid construction of data centers and AI computing clusters, even as Chinese buyers face U.S. export restrictions on advanced AI GPUs. Intel is set to announce its quarterly results on Thursday, with the CPU shortage expected to become a market focus.